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作者： Tang, Jun Shao, Ling Zhen, Xiantong Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Huangshan Road Hefei 230039 China College of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing 210044 China Department of Electronic and Electrical Engineering University of Sheffield Mappin Street Sheffield S1 3JD United Kingdom

Finding correspondences between two related feature point sets is a basic task in computer vision and pattern recognition. In this paper, we present a novel method for point pattern matching via spectral graph analysis. In particular, we aim to render the spectral matching algorithm more robust for positional jitter and outlier. A local structural descriptor, namely the spectral context, is proposed to describe the attribute domain of point sets, which is fundamentally different from the previous methods. Furthermore, the approximate distance order is defined and employed as the metric for geometric consistency of neighboring points in this work. By combining these two novel ingredients, we formulate feature point set matching as an optimization problem with one-to-one constraints. The correspondences are then obtained by maximizing the given objective function via the technique of probabilistic relaxation. Comparative experiments conducted on both synthetic and real data demonstrate the effectiveness of the proposed method, especially in the presence of positional jitter and outliers. © 2013 Elsevier Ltd. All rights reserved.

关键词： Jitter

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Twin Support Vector Machines Based on the Mixed Kernel Function

Twin Support Vector Machines Based on the Mixed Kernel Funct...

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The 6th International Conference on Computer Research and Development

作者： Fulin Wu Shifei Ding School of Computer Science and Technology China University of Mining and Technology Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences

The efficiency and performance of the Twin Support Vector Machines(TWSVM) are better than the traditional support vector machines when it deals with the problems. However, it also has the problem of selecting kernel functions. Generally, TWSVM selects the Gaussian radial basis kernel function. Although it has a strong learning ability, its generalization ability is relatively weak. In a certain extent, this will limit the performance of TWSVM. In order to solve the problem of selecting kernel functions in TWSVM, we propose the twin support vector machines based on the mixed kernel function(MK-TWSVM) in this paper. To make full use of the learning ability of local kernel functions and the excellent generalization ability of global kernel functions, MK-TWSVM selects a global kernel function and a local kernel function to construct a mixed kernel function which has the better performance. The experimental results indicate that the mixed kernel function makes TWSVM have the good learning ability and generalization ability. So it improves the performance of TWSVM.

关键词： mixed kernel function TWSVM kernel function

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Report on the FG 2015 Video Person Recognition Evaluation

Report on the FG 2015 Video Person Recognition Evaluation

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International Conference on Automatic Face and Gesture Recognition

作者： J. Ross Beveridge Hao Zhang Bruce A. Draper Patrick J. Flynn Zhenhua Feng Patrik Huber Josef Kittler Zhiwu Huang Shaoxin Li Yan Li Meina Kan Ruiping Wang Shiguang Shan Xilin Chen Haoxiang Li Gang Hua Vitomir Štruc Janez Križaj Changxing Ding Dacheng Tao P. Jonathon Phillips Colorado State University Fort Collins CO USA University of Notre Dame Notre Dame IN USA University of Surrey United Kingdom University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences Institute of Computing Technology CAS Beijing China Stevens Institute of Technology Hoboken NJ USA University of Ljubljana Ljubljana Slovenia Univerza v Ljubljani Ljubljana SI University of Technology Sydney Sydney Australia National Institute of Standards and Technology Gaithersburg MD USA

This report presents results from the Video Person Recognition Evaluation held in conjunction with the 11th IEEE International Conference on Automatic Face and Gesture Recognition. Two experiments required algorithms to recognize people in videos from the Point-and-Shoot Face Recognition Challenge Problem (PaSC). The first consisted of videos from a tripod mounted high quality video camera. The second contained videos acquired from 5 different handheld video cameras. There were 1401 videos in each experiment of 265 subjects. The subjects, the scenes, and the actions carried out by the people are the same in both experiments. Five groups from around the world participated in the evaluation. The video handheld experiment was included in the International Joint Conference on Biometrics (IJCB) 2014 Handheld Video Face and Person Recognition Competition. The top verification rate from this evaluation is double that of the top performer in the IJCB competition. Analysis shows that the factor most effecting algorithm performance is the combination of location and action: where the video was acquired and what the person was doing.

关键词： Face Feature extraction Face recognition Cameras Training Computational modeling

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Forecasting wheat aphid with remote sensing based on relevance vector machine

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Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 2015年第6期31卷 201-207页

作者： Tang, Cuicui Huang, Wenjiang Luo, Juhua Liang, Dong Zhao, Jinling Huang, Linsheng Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei230039 China School of Electronic and Information Engineering Anhui University Hefei230039 China Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing100094 China Nanjing Institute of Geography and Limnology Chinese Academy of Sciences Nanjing210008 China

The prevalence of aphid in winter wheat field has a significant impact on the production of winter wheat. An effective and timely forewarning of the scope and severity of the disease at a regional scale will not only reduce yield losses but also alert the stakeholders to take effective preventive measures. Forecasting aphid occurrence with Remote Sensing has great advantages over traditional methods and meteorological data, such as lower cost, simpler operation, more real-time and higher resolution. Chinese HJ-1A/1B data which have a high revisit frequency ( ©, 2015, Chinese Society of Agricultural Engineering. All right reserved.

关键词： Satellite imagery

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Non-fragile Observer Design for Fractional-order One-sided Lipschitz Nonlinear Systems

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International Journal of Automation and computing 2013年第4期10卷 296-302页

作者： Yong-Hong Lan Wen-Jie Li Yan Zhou Yi-Ping Luo School of Information Engineering Xiangtan University Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Institute of Intelligent Control Hunan Institute of Engineering

This paper is concerned with the problem of the full-order observer design for a class of fractional-order Lipschitz nonlinear systems. By introducing a continuous frequency distributed equivalent model and using an indirect Lyapunov approach, the sufficient condition for asymptotic stability of the full-order observer error dynamic system is presented. The stability condition is obtained in terms of LMI, which is less conservative than the existing one. A numerical example demonstrates the validity of this approach.

关键词： Fractional-order nonlinear system observer design indirect Lyapunov approach linear matrix inequality （LMI）.

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Base Station Planning Optimization Algorithm Based on Public Attitude

Base Station Planning Optimization Algorithm Based on Public...

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Wireless Communication and Sensor Network, Intl Conference on

作者： Yan-Ping Liu Wen-Zhong Guo Fei-Long Zhao College of Mathematics and Computer Science Fuzhou University Fujian China Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing Fuzhou University Fuzhou China

ISBN: (纸本)9781479970926

The problem of base station (BS) planning for TD-LTE network is studied in this paper. This method takes various factors into consideration according to the public attitude. The public attitude plays an important role in the process of BS planning. We choose the area where the network performance is the worst to build BS, according to public attitude, Monte Carlo method and least cost path analysis. The experience results show that after building a few BS, the network performance of planning area is generally good. The method has good application value.

关键词： Planning Monte Carlo methods Bills of materials Buildings Histograms Base stations Long Term Evolution

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A Survey of Commonsense Knowledge Acquisition

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Journal of Computer Science & Technology 2013年第4期28卷 689-719页

作者：臧良俊曹聪曹亚男吴昱明曹存根 Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences University of the Chinese Academy of Sciences The Second Lab Institute of Information Engineering Chinese Academy of Sciences

Collecting massive commonsense knowledge （CSK） for commonsense reasoning has been a long time standing challenge within artificial intelligence research. Numerous methods and systems for acquiring CSK have been developed to overcome the knowledge acquisition bottleneck. Although some specific commonsense reasoning tasks have been presented to allow researchers to measure and compare the performance of their CSK systems, we compare them at a higher level from the following aspects： CSK acquisition task （what CSK is acquired from where）, technique used （how can CSK be acquired）, and CSK evaluation methods （how to evaluate the acquired CSK）. In this survey, we first present a categorization of CSK acquisition systems and the great challenges in the field. Then, we review and compare the CSK acquisition systems in detail. Finally, we conclude the current progress in this field and explore some promising future research issues.

关键词： commonsense knowledge knowledge acquisition knowledge representation and reasoning

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Neural network based bilingual language model growing for statistical machine translation

Neural network based bilingual language model growing for st...

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2014 Conference on Empirical Methods in Natural Language processing, EMNLP 2014

作者： Wang, Rui Zhao, Hai Lu, Bao-Liang Utiyama, Masao Sumita, Eiichro Department of Computer Science and Engineering Center for Brain-Like Computing and Machine Intelligence Shanghai Jiao Tong University Shanghai200240 China Multilingual Translation Laboratory MASTAR Project National Institute of Information and Communications Technology 3-5 Hikaridai Keihanna Science City Kyoto619-0289 Japan Key Laboratory Shanghai Education Commission Intelligent Interaction Cognitive Engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781937284961

Since larger n-gram Language Model (LM) usually performs better in Statistical Machine Translation (SMT), how to construct efficient large LM is an important topic in SMT. However, most of the existing LM growing methods need an extra monolingual corpus, where additional LM adaption technology is necessary. In this paper, we propose a novel neural network based bilingual LM growing method, only using the bilingual parallel corpus in SMT. The results show that our method can improve both the perplexity score for LM evaluation and BLEU score for SMT, and significantly outperforms the existing LM growing methods without extra corpus. © 2014 Association for Computational Linguistics.

关键词： Neural networks

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Learning hierarchical translation spans

Learning hierarchical translation spans

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2014 Conference on Empirical Methods in Natural Language processing, EMNLP 2014

作者： Zhang, Jingyi Utiyama, Masao Sumita, Eiichro Zhao, Hai Department of Computer Science and Engineering Center for Brain-Like Computing and Machine Intelligence Shanghai Jiao Tong Unviersity Shanghai200240 China Key Laboratory Shanghai Education Commission Intelligent Interaction Cognitive Engineering Shanghai Jiao Tong Unviersity Shanghai200240 China National Institute of Information and Communications Technology 3-5Hikaridai Keihanna Science City Kyoto619-0289 Japan

ISBN: (纸本)9781937284961

We propose a simple and effective approach to learn translation spans for the hierarchical phrase-based translation model. Our model evaluates if a source span should be covered by translation rules during decoding, which is integrated into the translation system as soft constraints. Compared to syntactic constraints, our model is directly acquired from an aligned parallel corpus and does not require parsers. Rich source side contextual features and advanced machine learning methods were utilized for this learning task. The proposed approach was evaluated on NTCIR-9 Chinese-English and Japanese-English translation tasks and showed significant improvement over the baseline system. © 2014 Association for Computational Linguistics.

关键词： Syntactics

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Support vector machine with mixture of kernels for automatic image annotation

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High Technology Letters 2013年第3期19卷 295-300页

作者：田东平 Zhao Xiaofei Shi Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences

Automatic image annotation(AIA)has become an important and challenging problem in computer vision due to the existence of semantic *** this paper,a novel support vector machine with mixture of kernels(SVM-MK)for automatic image annotation is *** one hand,the combined global and local block-based image features are extracted in order to reflect the intrinsic content of images as complete as *** the other hand,SVM-MK is constructed to shoot for better annotating *** results on Corel dataset show that the proposed image feature representation method as well as automatic image annotation classifier,SVM-MK,can achieve higher annotating accuracy than SVM with any single kernel and mi-SVM for semantic image annotation.

关键词： automatic image annotation （ AIA） support vector machine （ SVM） kernel func-tion principal component analysis （PCA）

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